An investigation into Abdominal Aortic Aneurysm (AAA) rupture prediction

Cardiovascular Disease (CVD) is one of the leading causes of death and disability in the world. The mortality rate between 1993 -1997 in New Zealand was about 46% and 32% worldwide. CVDs such as Abdominal Aortic Aneurysm (AAA) is life threatening and poses a very high risk for aneurysm patients with particular aneurysm diameter. AAA rupture is a patient-specific problem with evolving structures and on-going growth. Current ultrasound methods are used to probe for and diagnose instantaneous AAA by analysing arterial tissue deformation. However, tracking the progression of potential aneurysms, and predicting their risk of rupturing based on the diameter of the aneurysm is still an insufficient method. AAA image segmentation and analysis using the Patient-Specific Aneurysm Rupture Predictor (P-SARP) protocol is proposed to identify dependent elements that lead to a three-dimensional (3-D) aneurysm reconstructive model. Models of the patient-specific aneurysm images were designed along with biomechanical characterization and specific material properties to be incorporated. Fluid Structure Interaction (FSI) is used to mathematically establish the oscillations of patient-specific cyclic pressure loading in order to visualize the impact of potential pressure distributions on the deformed arterial wall over time. The correlation between the geometric elements and the models’ potential for rupture are extensively investigated to produce a possible AAA rupture mechanism. This research presents a new Computational Fluid Dynamics (CFD) of Patient-Specific Aneurysm Model (PSAM) which is based on the energy strain function combined with the dilated vessel wall stress-strain relationship to predict aneurysm rupture. This thesis focuses on investigating how computer simulation can be incorporated to predict AAA rupture. The personalized model is developed based on instantaneous arterial deformations obtained from ultrasound images using a 6-9 MHz doppler transducer. The PSAM relies on available vii mechanical properties and parameters obtained from the personalised model. Using the strain energy function based on historical stress-strain relationship to extrapolate cyclic loading on the PSAM along with patient-specific pressure, multi variant factors are proposed and considered to predict the actual location of the weakening points to reach rupture. The material properties of the wall are calculated using biaxial tensile tests to observe the time dependency of the material response and formation of the aneurysm wall rupture. The outcomes indicate that the proposed technique of the PSAM model has the ability correlate the wall deformation and tissue failure mode with predicting rupture. Thus, this method can positively be integrated with already established ultrasound techniques for improvements in the accuracy of future diagnoses of potential AAA ruptures

Technology based learning system in Internet of Things (IoT) education

In this decade, Internet of Things (IoT) technologies are motivating nations for digital transformation. This transformation is part of Fourth industrial revolution (Industry 4.0). Several challenges are obstacle in the digitalization, one of them is talent in this field. There are not many available automation or control labs equipped with advance automation technologies in the educational institutions. To produce more force for IoT, engineering intuitions need to improve their curriculum and engineering lab facilities. In this paper, a technology-based learning system is proposed for learning IoT. The design of this system purposely developed for control lab for undergraduates and postgraduate students. This system offers a low-cost development using industrial standard controller, which is suitable for industrial and enterprise applications prototyping. Three modules are prepared to train the students; 1) Introduction to IoT & Industry 4.0, 2) controller programming, configuration and machine to machine (M2M) communication and 3) design and development of web and mobile applications. All students implemented and tested the industrial standard IoT application in the end of Session. The design and implementation result shows the learning experience of students has been improved and motivates the institutions to apply this low-cost system to fulfil the future talent demand in this field

Optimizing Mist-Based Ablution: A Comprehensive Study of Water Distribution and Conservation Using Watercolour Visualization and Thermal Imaging Techniques

Conducting ablution constitutes a prerequisite for Muslims prior to engaging in prayer. This ritualistic practice involves the cleansing and wiping of specific body parts, including the hands, face, arms up to the elbows, head, and feet. Ensuring comprehensive water coverage of the aforementioned areas is a crucial criterion during ablution. However, excessive water consumption often occurs when Muslims perform ablution to achieve full coverage. Consequently, a more ecologically sustainable approach to ablution is necessary to minimize water wastage. A proposed water mist spray device aims to optimize water usage while adhering to the Islamic jurisprudence requirements of complete water coverage on ablution parts. To assess water coverage using the mist spray, an evenness distribution profile is employed through atomized mist colorization on paper and thermal imaging of ablution parts. An appropriate spray nozzle is chosen based on an analysis of spray distribution and coverage patterns on the target surface, utilizing image processing techniques. The proposed methodology involves mixing water with red watercolour and manually pumping it through the selected nozzle using an off-the-shelf water sprayer, thereby atomizing the coloured water to stain white paper. Subsequently, the paper is converted into a digital image and analysed using ImageJ software to determine the mist spray coverage percentage, spatial spread at various distances, and the extraction of stain and droplet sizes. This technique is applied to different types and sizes of spray nozzles to identify the most suitable nozzle for the prototype. The findings demonstrate that nozzles with smaller exit holes and higher water pressure yield more extensive spray coverage on the target surface. Upon selecting the appropriate nozzle, a Portable Ablution Mist Spray Device prototype is employed to evaluate water coverage for the ablution body parts. Thermal images of the ablution parts are captured before and after the ritual, with the temperature differences being analysed. The thermal images reveal a comprehensive and uniform spray distribution on the ablution body parts, accompanied by a temperature difference ranging from 0.9°C to 3.8°C among various participants

Optimizing Mist-Based Ablution: A Comprehensive Study of Water Distribution and Conservation Using Watercolour Visualization and Thermal Imaging Techniques

Conducting ablution constitutes a prerequisite for Muslims prior to engaging in prayer. This ritualistic practice involves the cleansing and wiping of specific body parts, including the hands, face, arms up to the elbows, head, and feet. Ensuring comprehensive water coverage of the aforementioned areas is a crucial criterion during ablution. However, excessive water consumption often occurs when Muslims perform ablution to achieve full coverage. Consequently, a more ecologically sustainable approach to ablution is necessary to minimize water wastage. A proposed water mist spray device aims to optimize water usage while adhering to the Islamic jurisprudence requirements of complete water coverage on ablution parts. To assess water coverage using the mist spray, an evenness distribution profile is employed through atomized mist colorization on paper and thermal imaging of ablution parts. An appropriate spray nozzle is chosen based on an analysis of spray distribution and coverage patterns on the target surface, utilizing image processing techniques. The proposed methodology involves mixing water with red watercolour and manually pumping it through the selected nozzle using an off-the-shelf water sprayer, thereby atomizing the coloured water to stain white paper. Subsequently, the paper is converted into a digital image and analysed using ImageJ software to determine the mist spray coverage percentage, spatial spread at various distances, and the extraction of stain and droplet sizes. This technique is applied to different types and sizes of spray nozzles to identify the most suitable nozzle for the prototype. The findings demonstrate that nozzles with smaller exit holes and higher water pressure yield more extensive spray coverage on the target surface. Upon selecting the appropriate nozzle, a Portable Ablution Mist Spray Device prototype is employed to evaluate water coverage for the ablution body parts. Thermal images of the ablution parts are captured before and after the ritual, with the temperature differences being analysed. The thermal images reveal a comprehensive and uniform spray distribution on the ablution body parts, accompanied by a temperature difference ranging from 0.9°C to 3.8°C among various participants

Velocity control for spherical robot using PI-fuzzy logic

— This paper presents the finding on designing the fuzzy logic controller and analysis of the step input test on the model and control design. The PI-type fuzzy logic controller (FLC) was designed to control the velocity of the rolling spherical robot. The spherical robot model was tested with step input signal to analysis the effectiveness of the designed Fuzzy logic controller with 25-membership rule being constructed in Fuzzy toolbox MATLAB using triangular membership function and combination of gaussian and sigmoidal membership function. The output scaling factor (output gain) of FLC was tuned using Response Optimization toolbox and Particle Swarm Optimization to improve the system performance. Optimization using Matlab toolbox is done by specified the desired step response characteristics while in PSO, minimizing the Integral Absolute Error (IAE) is used as on objective of the optimization. The combined membership function shows better performance with less 8% overshoot, rise time less than 2s and settle at less than 3s after the response optimization process. Meanwhile, the PSO manage to tune the gain to reduce the IAE but contain large overshoot and longer settling time

Autonomous boat for underwater surveillance

Generally, an autonomous boat with vision ability faces difficulties in navigation and data processing. In this work, implementation on image processing in underwater environment is implemented using autonomous for surveillance purposes. In this endeavor, the focus will be on analyzing the use of single vision cameras in providing data for research on environmental front underwater and also detecting depth and obstacles for better navigation. The system is able to detect solid objects in underwater and it can provide different information of marine environment using correct algorithm and technique. The result is accurate enough to detect obstacles or objects above and beneath the water taking into account the diffraction of light needed for perfect vision. In this research, OpenCV library is used for digital image processing and color feature analysis rather than MATLAB due to the complexity for real time process. The design structure is mainly based on Pontoon style because it is more stable and reliable especially on the river wave condition. Moreover, additional sensors and actuators are implemented in this project to monitor underwater information for navigation purposes

Design and development of Multipurpose Educational and Research Platform (MERP) for learning control & IOT technologies

Vision TN50 “Transformasi Nasional 2050” is encouraging institutions to produce more talent for digitalization and transformation of Industries. This transformation opens a new domain for Internet of Things (IoT) technologies. Therefore, students are required to develops their skills and knowledge in the field of advance automation and robotics. There are a lot of automation or control labs available in the educational institutions that are not equipped with advance automation which are required for Internet of Things (IoT) technologies. This paper presents the design and development of a multipurpose educational and research platform (MERP) for learning IoT automation technologies. To develop a MERP, four requirements are outlined in this paper; (i) industrial standard controller to be used (ii) integration of the platform with the cloud computing (iii) develop a low-cost platform (iv) suitable for Industrial and Enterprise applications prototyping. To analyse the impact of MERP, students experience is evaluated on this developed platform in International Islamic University Malaysia (IIUM). The evaluation result shows the enormous improvement in student’s skills in term of learning new control technologies, especially Internet of Things (IoT). The proposed platform leverage students to design, control and develop IoT application that are in line with the industry 4.0

Features identification and classification of alphabet (ro) in leaning (Al-Inhiraf) and repetition (Al-Takrir) characteristics

—It is important for Muslim to recite the Quran properly with the correct Tajweed. which includes the use of correct characteristics (sifaat) and point of articulations (makhraj). To this date, there are limited researches done focusing on classifying the Quranic letters according to the characteristics. In this study, the focus is given to the classification of the characteristics of the Quranic letters for the purpose of developing an automated self-learning system for supporting the conventional method of Quranic teaching and learning. The characteristics of Quranic letters, which are the focus in this paper are Leaning and Repeating, where both consists of ر) ro) alphabet. Several methods of feature extractions and analysis were implemented such as Formant Analysis, Power Spectral Density (PSD), and Mel Frequency Cepstral Coefficient (MFCC) to come out with the suitable features that best represent the correct characteristics of the alphabet. Once the features had been identified, Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA) were used as the classifier. The results show that QDA with all 19 features trained achieved the highest percentage accuracy for both Leaning (اإلنحراف – Al-Inhiraf) and ّكرير) Repetition الت– Al-Takrir) characteristics with of 82.1% and 95.8% of accuracy respectivel

Design and material analysis of regenerative dispersion Magnetorheological (MR) damper

Magnetorheological (MR) dampers are widely applicable for vehicle suspension schemes, and MR fluid sedimentation is an indispensable problem of MR dampers. A Regenerative Dispersion MR Damper (RDMRD) under this research consists of a piston which contains piston and coil case cylinder, coil windings, piston rod, piston head cover, bobbin and one cylindrical tube to disperse MR fluids. In addition, external regeneration system has been added to generate electricity for the purpose of electricity supply in the piston. 2-D Axis symmetric model of RDMRD has been developed using Comsol Multiphysics in order to analyze power generation ability. Two magnetic field are generated inside the MR Damper, one internal piston coil and another external power producing coil. The induced magnetic field in the coil are evaluated for describing RDRMD power production capability

Lips tracking identification of a correct pronunciation of Quranic alphabets for tajweed teaching and learning

Mastering the recitation of the Holy Quran is an obligation among Muslims. It is an important task to fulfill other Ibadat like prayer, pilgrimage, and zikr. However, the traditional way of teaching Quran recitation is a hard task due to the extensive training time and effort required from both teacher and learner. In fact, learning the correct pronunciation of the Quranic letters or alphabets is the first step in mastering Tajweed (Rules and Guidance) in Quranic recitation. The pronunciation of Arabic alphabets is based on its points of articulation and the characteristics of a particular alphabet. In this paper, we implement a lip identification technique from video signal acquired from experts to extract the movement data of the lips while pronouncing the correct Quranic alphabets. The extracted lip movement data from experts helps in categorizing the alphabets into 5 groups and in deciding the final shape of the lips. Later, the technique was tested among a public reciter and then compared for similarity verification between the novice and the professional reciter. The system is able to extract the lip movement of the random user and draw the displacement graph and compare with the pronunciation of the expert. The error will be shown if the user has mistakenly pronounced the alphabet and suggests ways for improvement. More subjects with different backgrounds will be tested in the very near future with feedback instructions. Machine learning techniques will be implemented at a later stage for the real time learning application. Menguasai bacaan Al-Quran adalah satu kewajipan di kalangan umat Islam. Ia adalah satu tugas yang penting untuk memenuhi Ibadat lain seperti solat, haji, dan zikir. Walau bagaimanapun, cara tradisional pengajaran bacaan Al-Quran adalah satu tugas yang sukar kerana memerlukan masa latihan dan usaha yang banyak daripada guru dan pelajar. Malah, mempelajari sebutan yang betul bagi huruf Al-Quran adalah langkah pertama dalam menguasai Tajweed (Peraturan dan Panduan) pada bacaan Al-Quran. Sebutan huruf Arab adalah berdasarkan cara penyebutan tiap-tiap huruf dan ciri-ciri huruf tertentu. Dalam kertas ini, kami membina teknik pengenalan bibir dari isyarat video yang diperoleh daripada bacaan Al Quran oleh pakar-pakar untuk mengekstrak data pergerakan bibir ketika menyebut huruf Al-Quran yang betul. Data pergerakan bibir yang diekstrak daripada pembacaan oleh pakar membantu dalam mengkategorikan huruf kepada 5 kumpulan dan dalam menentukan bentuk akhir bibir. Kemudian, teknik ini diuji dengan pembaca awam dan kemudian bacaan mereka dibandingkan untuk pengesahan persamaan bacaan antara pembaca awam dan pembaca Al-Quran profesional. Sistem ini berjaya mengambil pergerakan bibir pengguna rawak dan melukis graf perbezaan sebutan mereka apabila dibandingkan dengan sebutan pakar. Jika pengguna telah tersilap menyebut sesuatu huruf, kesilapan akan ditunjukkan dan cara untuk penambahbaikan dicadangkan. Lebih ramai pengguna yang mempunyai latar belakang yang berbeza akan diuji dalam masa terdekat dan arahan maklum balas akan diberi. Teknik pembelajaran mesin akan dilaksanakan di peringkat seterusnya bagi penggunaan pembelajaran masa nyata